TLBO (Teaching Learning Based Optimization Algorithm) Search Algorithm

TLBO (Teaching Learning Based Optimization Algorithm) Search Algorithm:

TLBO search is an optimization algorithm used in Natural Language Processing. Teaching learning-based optimization (TLBO) is a population-based meta-heuristic optimization technique that simulates the environment of a classroom to optimize a given objective function and it was proposed by R.V. Rao et al. in 2011. Like other nature-inspired algorithms, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. The population is considered as a group of learners or a class of learners. 

The process of TLBO is divided into two parts: the first part consists of the ‘Teacher Phase’ and the second part consists of the ‘Learner Phase’. ‘Teacher Phase’ means learning from the teacher and ‘Learner Phase’ means learning by the interaction between learners. In a classroom, the teacher puts his hard work and makes all the learners of a class educated. Then the learners interact with themselves to further modify and improve their gained knowledge.

This algorithm consists of two phases:

1) Teacher phase

All the students learn from teacher and gain knowledge

2) Learner phase

Students interact among themselves to share knowledge with each other

Mathematical Model

1) Teaching phase

Student with minimum fitness value is considered as teacher

Xmean is used in this phase, where Xmean is the mean of all the students in the class

New solution generation equation :

Xnew = X + r*(Xteacher – TF*Xmean)

where TF is the teaching factor and is either 1 or 2 (chosen randomly)

If Xnew is better than X. Then replace X with Xnew

2) Learner phase

Xpartner: A randomly chosen fellow student from class

Xpartner is chosen to interact and exchange knowledge

New solution generation equation


Let fitness of Xparter is Fpartner and that of X is F

If(F < Fpartner )

Xnew = X + r*(X – Xpartner )

Else

Xnew = X – r*(X – Xpartner)

d. IF Xnew is better than X. Then replace X with Xnew








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